Along with a progress of technology of digital signal processing in recent years, voice communication through mobile phones in the outdoors, hands-free voice communication within automobiles, and hands-free operation by speech recognition are widely spread. Automatic monitoring systems have been also developed, which capture and detect screams or yells of people or abnormal sounds or vibrations generated by machines.
Devices that implement the foregoing functions are often used in a noisy environment, such as the outdoors or plants, or in a highly echoing environment where sound signals generated by speakers or other devices reach a microphone. Thus, unnecessary signals, such as background noise or sound echo signals, are also input together with a target signal to a sound transducer like a microphone or a vibration sensor. This action may result in deterioration of communication sound and a decrease in the voice recognition rate, the detection rate of abnormal sounds, and the like. Therefore, in order to implement comfortable voice communication, high-accuracy voice recognition, or high-accuracy abnormal sound detection, a sound signal enhancement device is needed, which is able to suppresses unnecessary signals included in an input signal (hereinafter, the foregoing unnecessary signals are referred to as “noise”) other than a target signal and enhances only the target signal.
Conventionally, there is a method using a neural network as a method for enhancing a target signal only (see, for example, Patent Literature 1). In the conventional method, a target signal is enhanced by improving the SN ratio of an input signal by using the neural network.